Website providers often desire to collect data that describes usage and visitation patterns for their websites. For example, website providers may collect information about how a visitor navigates through their website. This data is often referred to as web analytics data. Such information can be extremely valuable in developing usage statistics for various purposes, including for example estimating server load, determining advertising rates, identifying areas of websites that are in need of redesign, providing targeted advertising, and the like.
Often times, how the web analytics data is processed is specific to the requirements of an entity using the data. For instance, one retailer may prefer to place advertisements for a segment (e.g., type of customer, such as high-end shopper, soccer mom, etc.) in one manner whereas another retailer may prefer to place advertisements for the same segment in a different manner. Or segment classifications may vary from one retailer to another. As a result, the code to implement such processing may vary widely based on the retailer's preferences. Moreover, the person formulating those preferences is typically someone who may struggle to write the program code to implement those preferences.